Hasil untuk "Materials of engineering and construction. Mechanics of materials"

Yang Yang, Jaewoo Roh, Qian Zhang et al.

Soft actuators that combine compactness, rapid response, and high output power are critical for advancing high-performance soft robotic systems. Although bistable architectures can amplify speed through elastic instability, their combination with functional materials often sacrifices compactness or lacks tunability. Here, we report a Venus flytrap-inspired shape memory alloy – embedded snapping actuator (SMA-ESA) that achieves compact and tunable actuation by structurally integrating pre-shaped SMA wires within a double-tilted elastomeric matrix. The SMA skeleton not only triggers snap-through via its thermal shape memory effect but also regulates performance. Combined experimental and finite element studies reveal that the actuation performance – characterized by energy storage capacity as well as the rate and efficiency of energy release – is tunable through both geometric parameters and input power. As a proof of concept, the SMA-ESA is demonstrated in a flytrap-inspired capture device that selectively responds to external stimuli. These results establish a generalizable strategy for embedding high-power-density materials into bistable soft structures, offering new opportunities for compact, responsive, and bio-inspired soft robotics.

Danial Khatamsaz, Vahid Attari, Raymundo Arroyave

In this study, we propose a novel microstructure-sensitive Bayesian optimization (BO) framework designed to enhance the efficiency of materials discovery by explicitly incorporating microstructural information. Traditional materials design approaches often focus exclusively on direct chemistry-process-property relationships, overlooking the critical role of microstructures. To address this limitation, our framework integrates microstructural descriptors as latent variables, enabling the construction of a comprehensive process-structure-property mapping that improves both predictive accuracy and optimization outcomes. By employing the active subspace method for dimensionality reduction, we identify the most influential microstructural features, thereby reducing computational complexity while maintaining high accuracy in the design process. This approach also enhances the probabilistic modeling capabilities of Gaussian processes, accelerating convergence to optimal material configurations with fewer iterations and experimental observations. We demonstrate the efficacy of our framework through synthetic and real-world case studies, including the design of Mg$_2$Sn$_x$Si$_{1-x}$ thermoelectric materials for energy conversion. Our results underscore the critical role of microstructures in linking processing conditions to material properties, highlighting the potential of a microstructure-aware design paradigm to revolutionize materials discovery. Furthermore, this work suggests that since incorporating microstructure awareness improves the efficiency of Bayesian materials discovery, microstructure characterization stages should be integral to automated -- and eventually autonomous -- platforms for materials development.

Pradeep Raj Sharma, Bogeun Jang, Gaojie Zhang et al.

Spin-orbit torque (SOT) is a highly viable mechanism for achieving low-energy and high-speed switching in spintronic devices. Two-dimensional (2D) van der Waals (vdW) materials and their heterostructures have proven their scalability and energy effectiveness for device operation. Here, we demonstrate that SOT can be robustly realized in a heterostructure composed of the 2D-vdW ferromagnetic material (FM) Fe3GaTe2 (FGaT) and the 2D-vdW topological semimetal WTe2 at room temperature. The anisotropic Fermi surface originating from the uniquely reduced crystal symmetry of WTe2 enables field-free deterministic SOT switching. We report an unprecedentedly low threshold switching current density of 6.5 × 109 A m−2 at zero field and a spin Hall angle (θSH) of 8.5. These results demonstrate a nearly 100-fold improvement in device performance over all previously reported 3D heavy metal (HM)/FM systems, supported by a second harmonic-modulated nonlinear signal measurement implemented to ensure SOT analysis and reliability. The spin Hall conductivity (σSH) and the switching power density (Psw) reported are about 1.3 × 106 S m−1 and 0.33 × 1015 W m−3, respectively, supporting the efficient device performance at low power consumption. Our result highlights that Fe3GaTe2, coupled with the strong spin–orbit coupling and low crystal symmetry of WTe2, in the form of 2D-vdW heterostructure (WTe2/Fe3GaTe2), offers a promising platform for generating substantial torque on magnetization at room temperature. This leads to more efficient and easier switching, paving the way for developing next-generation, highly advanced, room-temperature spin-electronic devices.

Haiwei Gao, Nanxiang Zheng, Xiang Zhang et al.

To investigate the impact of mineral fiber modification and dosage on the rheological properties of fiber asphalt mastic, basalt fiber surface roughness was enhanced using nano-SiO _2 solution. Fiber asphalt mastic was prepared with a filler-bitumen ratio of 1.6 and fiber dosages of 0%, 1.3%, 2.6%, 3.9%, and 5.2%. The taper entry test, dynamic shear rheology test, and bending beam rheology test were employed to analyze the variations in taper entry, shear strength, complex modulus (G*), phase angle ( δ ), rutting factor (G*/sin δ ), modulus of strength (S), and rate of change of strength (m) of the fiber asphalt mastic. The results indicate that the optimal dosage of mineral fibers in fiber asphalt mastic is 2.6%. Nano-modified basalt fibers significantly enhance the anti-shear capacity of asphalt mastic. The high-temperature stability of fiber asphalt mastic improves with increasing fiber dosage, but the improvement becomes negligible beyond a 2.6% dosage. The interfacial bonding layer formed by asphalt on the fiber surface enhances the high-temperature performance and stress dissipation at low temperatures, thereby improving low-temperature cracking resistance.

Yuli Wang, Zonglei Wang, Junhong Yi et al.

Abstract Hydrogels emerge as a promising electrode material for scalp electroencephalogram monitoring, which stands as a pivotal technique in neuroscience, enabling real-time monitoring of brain activity. However, conventional hydrogel-enabled electrodes suffer from low scalp compliance, high scalp-electrode impedance, and inferior interfacial stability. Here, we propose an injectable eutectogel-enabled electrode for high-quality, long-term scalp electroencephalogram monitoring. This gelatin-based eutectogel exhibits temperature-controlled reversible phase transitions, enabling rapid in-situ gelation on the scalp and forming a robust self-adhesive interface. It demonstrates exceptional mechanical durability (1000 cycles at 100% strain), robust adhesion (0.7 N cm−1 on human epidermis and 1.7 N cm−1 on Ag/AgCl electrode), and outstanding anti-drying properties (negligible water loss after 7 days). Additionally, the eutectogel shows superior healing properties, antibacterial properties, and recyclability. Furthermore, it exhibits remarkably low scalp-electrode contact impedance (<20 kΩ at 16 Hz). The eutectogel is injected on the human scalp with dense hair for high-fidelity electroencephalogram recording, enabling long-term monitoring. Its practical applications include monitoring visual evoked potentials, steady-state visual evoked potentials, somatosensory evoked potentials, slow vertex response, auditory brainstem response, multi-channel cognitive electroencephalogram during various daily activities, and event-related potentials P300 signals. The eutectogel-enabled electrode provides a versatile and reliable solution for long-term electroencephalogram monitoring in diverse clinical and research settings.

Elmineh Tsegahun, Muluken Aklilu

Abstract In this study, we prepared zinc oxide nanoparticles using a quick, safe, and cost-effective method by reducing Zn(NO3)2·6H2O solution with Neem (Azadirachta indica) leaf extract. Qualitative phytochemical screening and FT-IR spectroscopy measurements were employed to validate the presence of active biomolecules such as Flavonoids, phenols, alkaloids, terpenes and tannic compounds. FT-IR, UV–Vis, and XRD spectroscopic techniques were utilized to fully analyze the biosynthesized nanoparticles. The spectrum of UV–Visible spectroscopy indicated UV–Vis spectrum of 321 nm. FTIR spectra showed the absorption peak for the stretching vibration of Zn–O at 544 cm−1. The results obtained supported the formation of ZnO NPs employing A. indica leaf extract as a reducing and stabilizing agent. X-ray diffraction spectrum analysis was also used to investigate the crystal structure. The particle size of ZnO NPs was calculated using the Scherrer’s equation and the result was found to be 19.16 nm. Furthermore, the antibacterial potential of zinc oxide nanoparticles against two clinical strains of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacteria was examined by paper disc diffusion method. The result showed a significant inhibition zone of 18 mm against E. coli and an inhibition zone of 15 mm against S. aureus. Graphical Abstract

Leonardo Sabattini, Annalisa Coriolano, Corneel Casert et al.

Two-dimensional (2D) materials are poised to revolutionize current solid-state technology with their extraordinary properties. Yet, the primary challenge remains their scalable production. While there have been significant advancements, much of the scientific progress has depended on the exfoliation of materials, a method that poses severe challenges for large-scale applications. With the advent of artificial intelligence (AI) in materials science, innovative synthesis methodologies are now on the horizon. This study explores the forefront of autonomous materials synthesis using an artificial neural network (ANN) trained by evolutionary methods, focusing on the efficient production of graphene. Our approach demonstrates that a neural network can iteratively and autonomously learn a time-dependent protocol for the efficient growth of graphene, without requiring pretraining on what constitutes an effective recipe. Evaluation criteria are based on the proximity of the Raman signature to that of monolayer graphene: higher scores are granted to outcomes whose spectrum more closely resembles that of an ideal continuous monolayer structure. This feedback mechanism allows for iterative refinement of the ANN's time-dependent synthesis protocols, progressively improving sample quality. Through the advancement and application of AI methodologies, this work makes a substantial contribution to the field of materials engineering, fostering a new era of innovation and efficiency in the synthesis process.

Thomas Wilhelm, Trang Thu Võ, Orkun Furat et al.

This paper introduces a novel method for characterizing fracture mechanisms in composite materials using 3D image data gained by computed tomography (CT) measurements. In mineral liberation, the understanding of these mechanisms is crucial, particularly whether fractures occur along the boundaries of mineral phases (intergranular fracture) and/or within mineral phases (transgranular fracture). Conventional techniques for analyzing fracture mechanisms are focused on globally comparing the surface exposure of mineral phases extracted from image measurements before and after fracture. Instead, we present a virtual reassembling algorithm based on image registration techniques, which is applied to 3D data of composite materials before and after fracture in order to determine and characterize the individual fracture surfaces. This enables us to conduct a local quantitative analysis of fracture mechanisms by voxelwise comparing adjacent regions at fracture surfaces. A quantitative analysis of fracture mechanisms is especially important in the context of geometallurgical recycling processes. As primary deposits are decreasing worldwide, the focus is shifting to secondary raw materials containing low concentrations of valuable elements such as lithium. To extract these elements, they can be enriched as engineered artificial minerals in the slag phase of appropriately designed cooling processes. The subsequent liberation through comminution processes, such as crushing, is essential for the extraction of valuable minerals. A better understanding of crushing processes, especially fracture mechanisms in slags, is crucial for the success of recycling. The reassembling algorithm presented in this paper is evaluated through a simulation study, followed by an application to a naturally occurring ore and a slag resulting from a recycling process.

Xinyi Jiang, Qingzheng Qiu, Cheng Peng et al.

Materials potentially hosting Kitaev spin-liquid states are considered crucial for realizing topological quantum computing. However, the intricate nature of spin interactions within these materials complicates the precise measurement of low-energy spin excitations indicative of fractionalized excitations. Using Na$_{2}$Co$_2$TeO$_{6}$ as an example, we study these low-energy spin excitations using the time-resolved resonant elastic x-ray scattering (tr-REXS). Our observations unveil remarkably slow spin dynamics at the magnetic peak, whose recovery timescale is several nanoseconds. This timescale aligns with the extrapolated spin gap of $\sim$ 1 $μ$eV, obtained by density matrix renormalization group (DMRG) simulations in the thermodynamic limit. The consistency demonstrates the efficacy of tr-REXS in discerning low-energy spin gaps inaccessible to conventional spectroscopic techniques.

Jing Chen, Changyi Zhou, Weilun Fang et al.

The commercially available drug-eluting stent with limus (rapamycin, everolimus, etc.) or paclitaxel inhibits smooth muscle cell (SMC), reducing the in-stent restenosis, whereas damages endothelial cell (EC) and delays stent reendothelialization, increasing the risk of stent thrombosis (ST) and sudden cardiac death. Here we present a new strategy for promoting stent reendothelialization and preventing ST by exploring the application of precise molecular targets with EC specificity. Proteomics was used to investigate the molecular mechanism of EC injury caused by rapamycin. Endothelial protein C receptor (EPCR) was screened out as a crucial EC-specific effector. Limus and paclitaxel repressed the EPCR expression, while overexpression of EPCR protected EC from coating (eluting) drug-induced injury. Furthermore, the ligand activated protein C (APC), polypeptide TR47, and compound parmodulin 2, which activated the target EPCR, promoted EC functions and inhibited platelet or neutrophil adhesion, and enhanced rapamycin stent reendothelialization in the simulated stent environment and in vitro. In vivo, the APC/rapamycin-coating promoted reendothelialization rapidly and prevented ST more effectively than rapamycin-coating alone, in both traditional metal stents and biodegradable stents. Additionally, overexpression or activation of the target EPCR did not affect the cellular behavior of SMC or the inhibitory effect of rapamycin on SMC. In conclusion, EPCR is a promising therapeutical agonistic target for pro-reendothelialization and anti-thrombosis of eluting stent. Activation of EPCR protects against coating drugs-induced EC injury, inflammatory cell, or platelet adhesion onto the stent. The novel application formula for APC/rapamycin-combined eluting promotes stent reendothelialization and prevents ST.

Mohammad Amin Molod, Panagiotis Spyridis, Franz-Joseph Barthold

Khalid El-Awady

We investigate the construction of generative models capable of encoding physical constraints that can be hard to express explicitly. For the problem of inverse material design, where one seeks to design a material with a prescribed set of properties, a significant challenge is ensuring synthetic viability of a proposed new material. We encode an implicit dataset relationships, namely that certain materials can be decomposed into other ones in the dataset, and present a VAE model capable of preserving this property in the latent space and generating new samples with the same. This is particularly useful in sequential inverse material design, an emergent research area that seeks to design a material with specific properties by sequentially adding (or removing) elements using policies trained through deep reinforcement learning.

G. B Olson, Z. K. Liu

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. As first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for the new technology of additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new "materials concurrency" integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

Andrii Iurov, Liubov Zhemchuzhna, Godfrey Gumbs et al.

We have established a rigorous theoretical formalism for Floquet engineering, or investigating and eventually tailoring most crucial electronic properties of tetragonal molybdenum disulfide (1T$^\prime$-MoS$_2$), by applying an external high-frequency dressing field in the off-resonant regime. It was recently demonstrated that monolayer semiconducting1T$^\prime$-MoS$_2$ may assume a distorted tetragonal structure which exhibits tunable and gapped spin- and valley-polarized tilted Dirac bandstructure. From the viewpoint of electronics, 1T$^\prime$-MoS$_2$ is one of the most technologically promising nanomaterials and a novel representative of an already famous family of transition metal dichalcogenides. The obtained dressed states strongly depend on the polarization of the applied irradiation and reflect the full complexity of the initial low-energy Hamiltonian of non-irradiated material. We have calculated and analyzed the obtained electron dressed states for linear and circular types of the polarization of the applied field focusing on their symmetrical properties, anisotropy, tilting and bandgaps, as well as topological signatures. Since a circularly polarized dressing field is also known to induce a transition into a new state with broken time-reversal symmetry and a non-zero Chern number, the combination of these topologically non-trivial phases and transitions between them could reveal some truly unique and earlier unknown phenomena.

Ananya Renuka Balakrishna

Intercalation materials are promising candidates for reversible energy storage and are, for example, used as lithium-battery electrodes, hydrogen-storage compounds, and electrochromic materials. An important issue preventing the more widespread use of these materials is that they undergo structural transformations (of up to ~10% lattice strains) during intercalation, which expand the material, nucleate microcracks, and, ultimately, lead to material failure. Besides the structural transformation of lattices, the crystallographic texture of the intercalation material plays a key role in governing ion-transport properties, generating phase separation microstructures, and elastically interacting with crystal defects. In this review, I provide an overview of how the structural transformation of lattices, phase transformation microstructures, and crystallographic defects affect the chemo-mechanical properties of intercalation materials. In each section, I identify the key challenges and opportunities to crystallographically design intercalation compounds to improve their properties and lifespans. I predominantly cite examples from the literature of intercalation cathodes used in rechargeable batteries, however, the identified challenges and opportunities are transferable to a broader range of intercalation compounds.

Silvan Gantenbein, Emanuele Colucci, Julian Käch et al.

Biological living materials, such as animal bones and plant stems, are able to self-heal, regenerate, adapt and make decisions under environmental pressures. Despite recent successful efforts to imbue synthetic materials with some of these remarkable functionalities, many emerging properties of complex adaptive systems found in biology remain unexplored in engineered living materials. Here, we report on a three-dimensional printing approach that harnesses the emerging properties of fungal mycelium to create living complex materials that self-repair, regenerate and adapt to the environment while fulfilling an engineering function. Hydrogels loaded with the fungus Ganoderma lucidum are 3D printed into lattice architectures to enable mycelial growth in a balanced exploration and exploitation pattern that simultaneously promotes colonization of the gel and bridging of air gaps. To illustrate the potential of such living complex materials, we 3D print a robotic skin that is mechanically robust, self-cleaning, and able to autonomously regenerate after damage.

Okin Song, Dongjoon Rhee, Jihyun Kim et al.

Abstract Inkjet printing is a cost-effective and scalable way to assemble colloidal materials into desired patterns in a vacuum- and lithography-free manner. Two-dimensional (2D) nanosheets are a promising material category for printed electronics because of their compatibility with solution processing for stable ink formulations as well as a wide range of electronic types from metal, semiconductor to insulator. Furthermore, their dangling bond-free surface enables atomically thin, electronically-active thin films with van der Waals contacts which significantly reduce the junction resistance. Here, we demonstrate all inkjet-printed thin-film transistors consisting of electrochemically exfoliated graphene, MoS2, and HfO2 as metallic electrodes, a semiconducting channel, and a high-k dielectric layer, respectively. In particular, the HfO2 dielectric layer is prepared via two-step; electrochemical exfoliation of semiconducting HfS2 followed by a thermal oxidation process to overcome the incompatibility of electrochemical exfoliation with insulating crystals. Consequently, all inkjet-printed 2D nanosheets with various electronic types enable high-performance, thin-film transistors which demonstrate field-effect mobilities and current on/off ratios of ~10 cm2 V−1 s−1 and >105, respectively, at low operating voltage.

Mustafa Maher Al-Tayeb, Yazan I. Abu Aisheh, Shaker M.A. Qaidi et al.

The impact of substantial amounts of plastic waste (PW) substituted fine aggregate (FA) on the mechanical characteristics of concrete under impact load (I.L) was studied experimentally-and-numerically. As fine aggregate substitutes, samples were made with 0%, 20%, 30%, and 40% PW. Six prisms of 100 mm width, 50 mm depth, and 400 mm length were loaded to failure in a drop-weight impact machine after 28 days by exposing them to 30 N of weight from a 400 mm height, while another three prisms of the same size and age were evaluated under static load(S.L). The load-displacement(L-D) and fracture energy(GF) of normal and concrete with PW prisms under S.L and I.L were investigated. A 3D finite element technique simulation was also carried out using LUSAS V.14 to investigate the impact of L-D behavior, and the predictions were confirmed by experimental findings. Despite reducing the fine aggregate amount, it was discovered that a proportionate increase of PW up to 20% can lead to improvements in bending load, impact tup, and inertial load.

Mohamed Attia Fouda, Amr Ibrahim, Mahmoud El-Kateb et al.

Strengthening of existing isolated footings using concrete jacketing is a traditional method to increase the load-carrying capacity and to enhance the performance of isolated footings. This paper presents a parametric study and a numerical validation for full-scale square footings strengthened with concrete jacketing, using either dowels and bonding agent or bonding agent only, to connect the existing and new concrete surfaces. A nonlinear finite element program “ABAQUS” was used for the numerical validation and the parametric investigation for various parameter's effect on the load-carrying capacity and contact stress redistribution underneath the strengthened footings. The parameters used in the parametric analysis include the ratio of the concrete jacket depth to the concrete footing depth, concrete compressive strength, spacing between dowels, and the ratio of the concrete jacket width to the concrete footing width. The effect of dowels on load carrying capacity of footings strengthened using a full concrete jacket is insignificant for jacket width smaller than the footing width. In footing strengthened using a full concrete jacket, the load carrying capacity increases by 9% compared to the non-strengthened footing.

Ahmad Zainul Ihsan, Danilo Dessì, Mehwish Alam et al.

The field of Materials Science is concerned with, e.g., properties and performance of materials. An important class of materials are crystalline materials that usually contain ``dislocations'' -- a line-like defect type. Dislocation decisively determine many important materials properties. Over the past decades, significant effort was put into understanding dislocation behavior across different length scales both with experimental characterization techniques as well as with simulations. However, for describing such dislocation structures there is still a lack of a common standard to represent and to connect dislocation domain knowledge across different but related communities. An ontology offers a common foundation to enable knowledge representation and data interoperability, which are important components to establish a ``digital twin''. This paper outlines the first steps towards the design of an ontology in the dislocation domain and shows a connection with the already existing ontologies in the materials science and engineering domain.